Capturing emergency dispatch address points as geocoding candidates to quantify delimited confidence in residential geolocation.

BACKGROUND: In response to citizens' concerns about elevated cancer incidence in their locales, US CDC proposed publishing cancer incidence at sub-county scales. At these scales, confidence in patients' residential geolocation becomes a key constraint of geospatial analysis. To support monitoring cancer incidence in sub-county areas, we presented summary metrics to numerically delimit confidence in residential geolocation. RESULTS: We defined a concept of Residential Address Discriminant Power (RADP) as theoretically perfect within all residential addresses and its practical application, i.e., using Emergency Dispatch (ED) Address Point Candidates of Equivalent Likelihood (CEL) to quantify Residential Geolocation Discriminant Power (RGDP) to approximate RADP. Leveraging different productivity of probabilistic, deterministic, and interactive geocoding record linkage, we simultaneously detected CEL for 5,807 cancer cases reported to North Carolina Central Cancer Registry (NC CCR)- in January 2022. Batch-match probabilistic and deterministic algorithms matched 86.0% cases to their unique ED address point candidates or a CEL, 4.4% to parcel site address, and 1.4% to street centerline. Interactively geocoded cases were 8.2%. To demonstrate differences in residential geolocation confidence between enumeration areas, we calculated sRGDP for cancer cases by county and assessed the existing uncertainty within the ED data, i.e., identified duplicate addresses (as CEL) for each ED address point in the 2014 version of the NC ED data and calculated ED_sRGDP by county. Both summary RGDP (sRGDP) (0.62-1.00) and ED_sRGDP (0.36-1.00) varied across counties and were lower in rural counties (p < 0.05); sRGDP correlated with ED_sRGDP (r = 0.42, p < 0.001). The discussion covered multiple conceptual and economic issues attendant to quantifying confidence in residential geolocation and presented a set of organizing principles for future work. CONCLUSIONS: Our methodology produces simple metrics - sRGDP - to capture confidence in residential geolocation via leveraging ED address points as CEL. Two facts demonstrate the usefulness of sRGDP as area-based summary metrics: sRGDP variability between counties and the overall lower quality of residential geolocation in rural vs. urban counties. Low sRGDP for the cancer cases within the area of interest helps manage expectations for the uncertainty in cancer incidence data. By supplementing cancer incidence data with sRGDP and ED_sRGDP, CCRs can demonstrate transparency in geocoding success, which may help win citizen trust.

The genomic landscape of familial glioma.

Glioma is a rare brain tumor with a poor prognosis. Familial glioma is a subset of glioma with a strong genetic predisposition that accounts for approximately 5% of glioma cases. We performed whole-genome sequencing on an exploratory cohort of 203 individuals from 189 families with a history of familial glioma and an additional validation cohort of 122 individuals from 115 families. We found significant enrichment of rare deleterious variants of seven genes in both cohorts, and the most significantly enriched gene was HERC2 (P = 0.0006). Furthermore, we identified rare noncoding variants in both cohorts that were predicted to affect transcription factor binding sites or cause cryptic splicing. Last, we selected a subset of discovered genes for validation by CRISPR knockdown screening and found that DMBT1, HP1BP3, and ZCH7B3 have profound impacts on proliferation. This study performs comprehensive surveillance of the genomic landscape of familial glioma.

Attribute Associations as a Practical Approach to Account for Uncertainty in Residential Geolocation of Cancer Surveillance Data.

This methodology article proposes a basic framework for assessing confidence in residential address through attribute sets of the tumor record that enable or modify spatiotemporal relationships in cancer surveillance data. A first step in assessing confidence for a statutory downstream data steward, like the Central Cancer Registry (CCR), is identifying sets of attributes whose domains are independently controlled by data stewards outside of the CCR. These include attribute sets that comprise the digital entities of person, time, and place. In this article, we describe the uncertainty in the geolocation of a cancer patient at the time of diagnosis, focusing on multiple stewardship of the cancer surveillance data. We also propose an approach to account for this uncertainty that is practical within the framework of existing cancer registry data coding, processing conventions, and legislative mandates for cancer surveillance.

Geospatial analysis of multiple cancers in individuals in the US, 2004-2014.

BACKGROUND: There is a projected rapid increase in cancer survivors in the US population, from 15.5 million in 2016 to 26.1 million by 2040. Improvements in treatment and detection have led to increased survival, however, there is now a risk of developing new cancers as a result of environment toxins, behavioral risk factors, genetic predisposition, and late-term effects of radiation and chemotherapeutic treatments. This study takes a geospatial approach to examining the place of occurrence of multiple cancers originating in the population of four screenable cancers-female breast, colorectal, prostate, and cervical cancers-among the US population. METHODS: During 2004-2014, 6,523,532 primary cancer patients with one of these four screenable cancers were examined, and subsequent primary cancers (multiple cancers of any type) were noted. Individual level analyses estimated the odds of diagnosis with multiple cancers controlling for age, sex, and race-ethnicity. Change in effects on odds of multiple cancer diagnoses with age, sex, and race-ethnicity were evaluated controlling separately for late-stage diagnosis of the primary cancer or each primary cancer diagnosis type. County-level spatial cluster analysis was employed to identify and visualize higher than average multiple cancer rates. RESULTS: Over half of the study population were female and almost 30% of the study population were diagnosed at late-stage for their first cancer. Multiple occurrences of all cancers increased during the time period for patients with initial breast or colorectal cancers. Among BC primary cancer cases, subsequent multiple cancers were mostly new breast cancers. By contrast, for CRC primary cancer cases, subsequent multiple cancers were about equally likely to be new CRC cases or other cancer types. Sex, age and race-ethnicity were all significantly associated with multiple cancers. In the model controlling for CRC as the primary type, the age and race-ethnicity effects were somewhat different than for all the other models. Thus, there was something distinctly different about the multiple cancer incidence among patients with CRC as their primary cancer as compared to patients with BC, CVC, or PC primaries. In subsequent analyses by county, there were distinct geospatial patterns in multiple cancer rates with most high-rate clusters occurring in the north- and mid-west US. CONCLUSIONS: There were distinct individual level and geospatial disparities in multiple cancer diagnoses for the study population of all primary breast, colorectal, cervical, or prostate cancer patients during the decade studied. It is importance to emphasize continued screening for cancer survivors and research on personal and environmental drivers of multiple primary cancers.

Increasing Incidence of Liposarcoma: A Population-Based Study of National Surveillance Databases, 2001-2016.

Rare cancers, affecting 1 in 5 cancer patients, disproportionally contribute to cancer mortality. This research focuses on liposarcoma, an understudied rare cancer with unknown risk factors and limited treatment options. Liposarcoma incident cases were identified from the U.S. Surveillance, Epidemiology, and End Result (SEER) program and the combined SEER-National Program of Cancer Registries (CNPCR) between 2001-2016. Incidence rates (age-adjusted and age-specific), 5-year survival, and the time trends were determined using SEER*stat software. Three-dimensional visualization of age-time curves was conducted for males and females. SEER liposarcoma cases represented ~30% (n = 11,162) of the nationwide pool (N = 37,499). Both sources of data showed males accounting for ~60% of the cases; 82%-86% cases were identified among whites. Age-adjusted incidence was greater among males vs. females and whites vs. blacks, whereas survival did not differ by sex and race. The dedifferentiated (57.2%), pleomorphic (64.1%), and retroperitoneal (63.9%) tumors had the worse survival. Nationwide, liposarcoma rates increased by 19%, with the annual percent increase (APC) of 1.43% (95% confidence interval (CI): 1.12-1.74). The APC was greater for males vs. females (1.67% vs. 0.89%) and retroperitoneal vs. extremity tumors (1.94% vs. 0.58%). Thus, incidence increased faster in the high-risk subgroup (males), and for retroperitoneal tumors, the low-survival subtype. The SEER generally over-estimated the rates and time trends compared to nationwide data but under-estimated time trends for retroperitoneal tumors. The time trends suggest an interaction between genetic and non-genetic modifiable risk factors may play a role in the etiology of this malignancy. Differences between SEER and CNCPR findings emphasize the need for nationwide cancer surveillance.

Glioma risk associated with extent of estimated European genetic ancestry in African Americans and Hispanics.

Glioma incidence is highest in non-Hispanic Whites, and to date, glioma genome-wide association studies (GWAS) to date have only included European ancestry (EA) populations. African Americans and Hispanics in the US have varying proportions of EA, African (AA) and Native American ancestries (NAA). It is unknown if identified GWAS loci or increased EA is associated with increased glioma risk. We assessed whether EA was associated with glioma in African Americans and Hispanics. Data were obtained for 832 cases and 675 controls from the Glioma International Case-Control Study and GliomaSE Case-Control Study previously estimated to have <80% EA, or self-identify as non-White. We estimated global and local ancestry using fastStructure and RFMix, respectively, using 1,000 genomes project reference populations. Within groups with ≥40% AA (AFR≥0.4 ), and ≥15% NAA (AMR≥0.15 ), genome-wide association between local EA and glioma was evaluated using logistic regression conditioned on global EA for all gliomas. We identified two regions (7q21.11, p = 6.36 × 10-4 ; 11p11.12, p = 7.0 × 10-4 ) associated with increased EA, and one associated with decreased EA (20p12.13, p = 0.0026) in AFR≥0.4 . In addition, we identified a peak at rs1620291 (p = 4.36 × 10-6 ) in 7q21.3. Among AMR≥0.15 , we found an association between increased EA in one region (12q24.21, p = 8.38 × 10-4 ), and decreased EA in two regions (8q24.21, p = 0. 0010; 20q13.33, p = 6.36 × 10-4 ). No other significant associations were identified. This analysis identified an association between glioma and two regions previously identified in EA populations (8q24.21, 20q13.33) and four novel regions (7q21.11, 11p11.12, 12q24.21 and 20p12.13). The identifications of novel association with EA suggest regions to target for future genetic association studies.

Lack of association between modifiable exposures and glioma risk: a Mendelian randomization analysis.

BACKGROUND: The etiological basis of glioma is poorly understood. We have used genetic markers in a Mendelian randomization (MR) framework to examine if lifestyle, cardiometabolic, and inflammatory factors influence the risk of glioma. This methodology reduces bias from confounding and is not affected by reverse causation. METHODS: We identified genetic instruments for 37 potentially modifiable risk factors and evaluated their association with glioma risk using data from a genome-wide association study of 12 488 glioma patients and 18 169 controls. We used the estimated odds ratio of glioma associated with each of the genetically defined traits to infer evidence for a causal relationship with the following exposures:Lifestyle and dietary factors-height, plasma insulin-like growth factor 1, blood carnitine, blood methionine, blood selenium, blood zinc, circulating adiponectin, circulating carotenoids, iron status, serum calcium, vitamins (A1, B12, B6, E, and 25-hydroxyvitamin D), fatty acid levels (monounsaturated, omega-3, and omega-6) and circulating fetuin-A;Cardiometabolic factors-birth weight, high density lipoprotein cholesterol, low density lipoprotein cholesterol, total cholesterol, total triglycerides, basal metabolic rate, body fat percentage, body mass index, fasting glucose, fasting proinsulin, glycated hemoglobin levels, diastolic and systolic blood pressure, waist circumference, waist-to-hip ratio; andInflammatory factors- C-reactive protein, plasma interleukin-6 receptor subunit alpha and serum immunoglobulin E. RESULTS: After correction for the testing of multiple potential risk factors and excluding associations driven by one single nucleotide polymorphism, no significant association with glioma risk was observed (ie, PCorrected > 0.05). CONCLUSIONS: This study did not provide evidence supporting any of the 37 factors examined as having a significant influence on glioma risk.

Update on triple-negative breast cancer disparities for the United States: A population-based study from the United States Cancer Statistics database, 2010 through 2014.

BACKGROUND: Triple-negative breast cancer (TNBC) has been associated with a more aggressive histology, poorer prognosis, and nonresponsiveness to hormone therapy. It is imperative that cancer research identify factors that drive disparities and focus on prevention. METHODS: Using the United States Cancer Statistics database, the authors examined differences between TNBCs compared with all other breast cancers with regard to age, race/ethnicity, and stage at diagnosis. RESULTS: A total of 1,151,724 cases of breast cancer were identified from 2010 through 2014, with the triple-negative phenotype accounting for approximately 8.4% of all cases. In unadjusted analyses, non-Hispanic black women (odds ratio [OR], 2.27; 95% CI, 2.23-2.31) and Hispanic women (OR, 1.22; 95% CI, 1.19-1.25) had higher odds of diagnosis when compared with non-Hispanic white women. Women aged <40 years had the highest odds of diagnosis compared with women aged 50 to 64 years (OR, 1.95; 95% CI, 1.90-2.01). Diagnosis at American Joint Committee on Cancer stage III and beyond conferred higher odds of the diagnosis of TNBC (OR for stage III, 1.69 [95% CI, 1.68-1.72]; and OR for stage IV, 1.47 [95% CI, 1.43-1.51]). Results varied slightly in adjusted analyses. CONCLUSIONS: The results of the current study demonstrated that there is a significant burden of disease in TNBC diagnosed among women of color, specifically non-Hispanic black women, and younger women. Additional studies are needed to determine drivers of disparities between race, age, and stage of disease at diagnosis.

Publisher Correction: Mendelian randomisation study of the relationship between vitamin D and risk of glioma.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

Transcriptome-Wide Association Study Identifies New Candidate Susceptibility Genes for Glioma.

Genome-wide association studies (GWAS) have so far identified 25 loci associated with glioma risk, with most showing specificity for either glioblastoma (GBM) or non-GBM tumors. The majority of these GWAS susceptibility variants reside in noncoding regions and the causal genes underlying the associations are largely unknown. Here we performed a transcriptome-wide association study to search for novel risk loci and candidate causal genes at known GWAS loci using Genotype-Tissue Expression Project (GTEx) data to predict cis-predicted gene expression in relation to GBM and non-GBM risk in conjunction with GWAS summary statistics on 12,488 glioma cases (6,183 GBM and 5,820 non-GBM) and 18,169 controls. Imposing a Bonferroni-corrected significance level of P < 5.69 × 10-6, we identified 31 genes, including GALNT6 at 12q13.33, as a candidate novel risk locus for GBM (mean Z = 4.43; P = 5.68 × 10-6). GALNT6 resides at least 55 Mb away from any previously identified glioma risk variant, while all other 30 significantly associated genes were located within 1 Mb of known GWAS-identified loci and were not significant after conditioning on the known GWAS-identified variants. These data identify a novel locus (GALNT6 at 12q13.33) and 30 genes at 12 known glioma risk loci associated with glioma risk, providing further insights into glioma tumorigenesis. SIGNIFICANCE: This study identifies new genes associated with glioma risk, increasing understanding of how these tumors develop.

Sex-specific gene and pathway modeling of inherited glioma risk.

Background: To date, genome-wide association studies (GWAS) have identified 25 risk variants for glioma, explaining 30% of heritable risk. Most histologies occur with significantly higher incidence in males, and this difference is not explained by currently known risk factors. A previous GWAS identified sex-specific glioma risk variants, and this analysis aims to further elucidate risk variation by sex using gene- and pathway-based approaches. Methods: Results from the Glioma International Case-Control Study were used as a testing set, and results from 3 GWAS were combined via meta-analysis and used as a validation set. Using summary statistics for nominally significant autosomal SNPs (P < 0.01 in a previous meta-analysis) and nominally significant X-chromosome SNPs (P < 0.01), 3 algorithms (Pascal, BimBam, and GATES) were used to generate gene scores, and Pascal was used to generate pathway scores. Results were considered statistically significant in the discovery set when P < 3.3 × 10-6 and in the validation set when P < 0.001 in 2 of 3 algorithms. Results: Twenty-five genes within 5 regions and 19 genes within 6 regions reached statistical significance in at least 2 of 3 algorithms in males and females, respectively. EGFR was significantly associated with all glioma and glioblastoma in males only and a female-specific association in TERT, all of which remained nominally significant after conditioning on known risk loci. There were nominal associations with the BioCarta telomeres pathway in both males and females. Conclusions: These results provide additional evidence that there may be differences by sex in genetic risk for glioma. Additional analyses may further elucidate the biological processes through which this risk is conferred.

Aspirin, NSAIDs, and Glioma Risk: Original Data from the Glioma International Case-Control Study and a Meta-analysis.

BACKGROUND: There have been few studies of sufficient size to address the relationship between glioma risk and the use of aspirin or NSAIDs, and results have been conflicting. The purpose of this study was to examine the associations between glioma and aspirin/NSAID use, and to aggregate these findings with prior published studies using meta-analysis. METHODS: The Glioma International Case-Control Study (GICC) consists of 4,533 glioma cases and 4,171 controls recruited from 2010 to 2013. Interviews were conducted using a standardized questionnaire to obtain information on aspirin/NSAID use. We examined history of regular use for ≥6 months and duration-response. Restricted maximum likelihood meta-regression models were used to aggregate site-specific estimates, and to combine GICC estimates with previously published studies. RESULTS: A history of daily aspirin use for ≥6 months was associated with a 38% lower glioma risk, compared with not having a history of daily use [adjusted meta-OR = 0.62; 95% confidence interval (CI), 0.54-0.70]. There was a significant duration-response trend (P = 1.67 × 10-17), with lower ORs for increasing duration of aspirin use. Duration-response trends were not observed for NSAID use. In the meta-analysis aggregating GICC data with five previous studies, there was a marginally significant association between use of aspirin and glioma (mOR = 0.84; 95% CI, 0.70-1.02), but no association for NSAID use. CONCLUSIONS: Our study suggests that aspirin may be associated with a reduced risk of glioma. IMPACT: These results imply that aspirin use may be associated with decreased glioma risk. Further research examining the association between aspirin use and glioma risk is warranted.

Age-specific genome-wide association study in glioblastoma identifies increased proportion of 'lower grade glioma'-like features associated with younger age.

Glioblastoma (GBM) is the most common malignant brain tumor in the United States. Incidence of GBM increases with age, and younger age-at-diagnosis is significantly associated with improved prognosis. While the relationship between candidate GBM risk SNPs and age-at-diagnosis has been explored, genome-wide association studies (GWAS) have not previously been stratified by age. Potential age-specific genetic effects were assessed in autosomal SNPs for GBM patients using data from four previous GWAS. Using age distribution tertiles (18-53, 54-64, 65+) datasets were analyzed using age-stratified logistic regression to generate p values, odds ratios (OR), and 95% confidence intervals (95%CI), and then combined using meta-analysis. There were 4,512 total GBM cases, and 10,582 controls used for analysis. Significant associations were detected at two previously identified SNPs in 7p11.2 (rs723527 [p54-63 = 1.50x10-9 , OR54-63 = 1.28, 95%CI54-63 = 1.18-1.39; p64+ = 2.14x10-11 , OR64+ = 1.32, 95%CI64+ = 1.21-1.43] and rs11979158 [p54-63 = 6.13x10-8 , OR54-63 = 1.35, 95%CI54-63 = 1.21-1.50; p64+ = 2.18x10-10 , OR64+ = 1.42, 95%CI64+ = 1.27-1.58]) but only in persons >54. There was also a significant association at the previously identified lower grade glioma (LGG) risk locus at 8q24.21 (rs55705857) in persons ages 18-53 (p18-53 = 9.30 × 10-11 , OR18-53 = 1.76, 95%CI18-53 = 1.49-2.10). Within The Cancer Genome Atlas (TCGA) there was higher prevalence of 'LGG'-like tumor characteristics in GBM samples in those 18-53, with IDH1/2 mutation frequency of 15%, as compared to 2.1% [54-63] and 0.8% [64+] (p = 0.0005). Age-specific differences in cancer susceptibility can provide important clues to etiology. The association of a SNP known to confer risk for IDH1/2 mutant glioma and higher prevalence of IDH1/2 mutation within younger individuals 18-53 suggests that more younger individuals may present initially with 'secondary glioblastoma.'

Application of mutagen sensitivity assay in a glioma case-control study.

Few risk factors for glioma have been identified other than ionizing radiation. The alkylating agent acrylamide is a compound found in both occupational and the general environment and identified as one of the forty known or suspected neurocarcinogens in animal models. The mutagen sensitivity assay (MSA) has been used to indirectly show reduced DNA repair capacity upon exposure to ionizing radiation in those with glioma compared to controls. In this study, MSA was used to assess its applicability to a glioma case-control study and to test the hypothesis that subjects with glioma may have lower DNA repair capacity after exposure to selected potential human neurocarcinogens (i.e. acrylamide), compared to controls. Approximately 50 case and 50 control subjects were identified from a clinic-based study that investigated environmental risk factors for glioma, who completed an exposure survey, and had frozen immortalized lymphocytes available. A total of 50 metaphase spreads were read and reported for each participant. The association of case-control status with MSA for acrylamide, i.e. breaks per spread, was examined by multivariable logistic regression models. The mean number of breaks per slide was similar between hospital-based controls and cases. In addition, case-control status or exposure categories were not associated with the number of breaks per spread. Although the MSA has been shown as a useful molecular epidemiology tool for identifying individuals at higher risk for cancer, our data do not support the hypothesis that glioma patients have reduced DNA repair capacity in response to exposure to acrylamide. Further research is needed before the MSA is utilized in large-scale epidemiological investigations of alkylating agents.

Sex-specific glioma genome-wide association study identifies new risk locus at 3p21.31 in females, and finds sex-differences in risk at 8q24.21.

Incidence of glioma is approximately 50% higher in males. Previous analyses have examined exposures related to sex hormones in women as potential protective factors for these tumors, with inconsistent results. Previous glioma genome-wide association studies (GWAS) have not stratified by sex. Potential sex-specific genetic effects were assessed in autosomal SNPs and sex chromosome variants for all glioma, GBM and non-GBM patients using data from four previous glioma GWAS. Datasets were analyzed using sex-stratified logistic regression models and combined using meta-analysis. There were 4,831 male cases, 5,216 male controls, 3,206 female cases and 5,470 female controls. A significant association was detected at rs11979158 (7p11.2) in males only. Association at rs55705857 (8q24.21) was stronger in females than in males. A large region on 3p21.31 was identified with significant association in females only. The identified differences in effect of risk variants do not fully explain the observed incidence difference in glioma by sex.

Glioma-related seizures in relation to histopathological subtypes: a report from the glioma international case-control study.

BACKGROUND: The purpose of this study was to evaluate the distribution of glioma-related seizures and seizure control at the time of tumor diagnosis with respect to tumor histologic subtypes, tumor treatment and patient characteristics, and to compare seizure history preceding tumor diagnosis (or study enrollment) between glioma patients and healthy controls. METHODS: The Glioma International Case Control study (GICC) risk factor questionnaire collected information on demographics, past medical/medication history, and occupational history. Cases from eight centers were also asked detailed questions on seizures in relation to glioma diagnosis; cases (n = 4533) and controls (n = 4171) were also asked about seizures less than 2 years from diagnosis and previous seizure history more than 2 years prior to tumor diagnosis, including childhood seizures. RESULTS: Low-grade gliomas (LGGs), particularly oligodendrogliomas/oligoastrocytomas, had the highest proportion of glioma-related seizures. Patients with low-grade astrocytoma demonstrated the most medically refractory seizures. A total of 83% of patients were using only one antiepileptic drug (AED), which was levetiracetam in 71% of cases. Gross total resection was strongly associated with reduced seizure frequency (p < 0.009). No significant difference was found between glioma cases and controls in terms of seizure occurring more than 2 years before diagnosis or during childhood. CONCLUSIONS: Our study showed that glioma-related seizures were most common in low-grade gliomas. Gross total resection was associated with lower seizure frequency. Additionally, having a history of childhood seizures is not a risk factor ***for developing glioma-related seizures or glioma.

Influence of obesity-related risk factors in the aetiology of glioma.

BACKGROUND: Obesity and related factors have been implicated as possible aetiological factors for the development of glioma in epidemiological observation studies. We used genetic markers in a Mendelian randomisation framework to examine whether obesity-related traits influence glioma risk. This methodology reduces bias from confounding and is not affected by reverse causation. METHODS: Genetic instruments were identified for 10 key obesity-related risk factors, and their association with glioma risk was evaluated using data from a genome-wide association study of 12,488 glioma patients and 18,169 controls. The estimated odds ratio of glioma associated with each of the genetically defined obesity-related traits was used to infer evidence for a causal relationship. RESULTS: No convincing association with glioma risk was seen for genetic instruments for body mass index, waist-to-hip ratio, lipids, type-2 diabetes, hyperglycaemia or insulin resistance. Similarly, we found no evidence to support a relationship between obesity-related traits with subtypes of glioma-glioblastoma (GBM) or non-GBM tumours. CONCLUSIONS: This study provides no evidence to implicate obesity-related factors as causes of glioma.

Impact of atopy on risk of glioma: a Mendelian randomisation study.

BACKGROUND: An inverse relationship between allergies with glioma risk has been reported in several but not all epidemiological observational studies. We performed an analysis of genetic variants associated with atopy to assess the relationship with glioma risk using Mendelian randomisation (MR), an approach unaffected by biases from temporal variability and reverse causation that might have affected earlier investigations. METHODS: Two-sample MR was undertaken using genome-wide association study data. We used single nucleotide polymorphisms (SNPs) associated with atopic dermatitis, asthma and hay fever, IgE levels, and self-reported allergy as instrumental variables. We calculated MR estimates for the odds ratio (OR) for each risk factor with glioma using SNP-glioma estimates from 12,488 cases and 18,169 controls, using inverse-variance weighting (IVW), maximum likelihood estimation (MLE), weighted median estimate (WME) and mode-based estimate (MBE) methods. Violation of MR assumptions due to directional pleiotropy were sought using MR-Egger regression and HEIDI-outlier analysis. RESULTS: Under IVW, MLE, WME and MBE methods, associations between glioma risk with asthma and hay fever, self-reported allergy and IgE levels were non-significant. An inverse relationship between atopic dermatitis and glioma risk was found by IVW (OR 0.96, 95% confidence interval (CI) 0.93-1.00, P = 0.041) and MLE (OR 0.96, 95% CI 0.94-0.99, P = 0.003), but not by WME (OR 0.96, 95% CI 0.91-1.01, P = 0.114) or MBE (OR 0.97, 95% CI 0.92-1.02, P = 0.194). CONCLUSIONS: Our investigation does not provide strong evidence for relationship between atopy and the risk of developing glioma, but findings do not preclude a small effect in relation to atopic dermatitis. Our analysis also serves to illustrate the value of using several MR methods to derive robust conclusions.

Mendelian randomisation study of the relationship between vitamin D and risk of glioma.

To examine for a causal relationship between vitamin D and glioma risk we performed an analysis of genetic variants associated with serum 25-hydroxyvitamin D (25(OH)D) levels using Mendelian randomisation (MR), an approach unaffected by biases from confounding. Two-sample MR was undertaken using genome-wide association study data. Single nucleotide polymorphisms (SNPs) associated with 25(OH)D levels were used as instrumental variables (IVs). We calculated MR estimates for the odds ratio (OR) for 25(OH)D levels with glioma using SNP-glioma estimates from 12,488 cases and 18,169 controls, using inverse-variance weighted (IVW) and maximum likelihood estimation (MLE) methods. A non-significant association between 25(OH)D levels and glioma risk was shown using both the IVW (OR = 1.21, 95% confidence interval [CI] = 0.90-1.62, P = 0.201) and MLE (OR = 1.20, 95% CI = 0.98-1.48, P = 0.083) methods. In an exploratory analysis of tumour subtype, an inverse relationship between 25(OH)D levels and glioblastoma (GBM) risk was identified using the MLE method (OR = 0.62, 95% CI = 0.43-0.89, P = 0.010), but not the IVW method (OR = 0.62, 95% CI = 0.37-1.04, P = 0.070). No statistically significant association was shown between 25(OH)D levels and non-GBM glioma. Our results do not provide evidence for a causal relationship between 25(OH)D levels and all forms of glioma risk. More evidence is required to explore the relationship between 25(OH)D levels and risk of GBM.

Geospatial Analysis of Inflammatory Breast Cancer and Associated Community Characteristics in the United States.

Inflammatory breast cancer (IBC) is a rare and aggressive form of breast cancer, almost always diagnosed at late stage where mortality outcomes and morbidity burdens are known to be worse. Missed by mammography screening, IBC progresses rapidly and reaches late stage by the time of diagnosis. With an unknown etiology and poor prognosis, it is crucial to evaluate the distribution of the disease in the population as well as identify area social and economic contextual risk factors that may be contributing to the observed patterns of IBC incidence. In this study, we identified spatial clustering of county-based IBC rates among US females and examined the underlying community characteristics associated with the clusters. IBC accounted for ~1.25% of all primary breast cancers diagnoses in 2004-2012 and was defined by the Collaborative Stage (CS) Extension code 710 and 730. Global and local spatial clusters of IBC rates were identified and mapped. The Mann-Whitney U test was used to compare median differences in key contextual variables between areas with high and low spatial clusters of IBC rates. High clusters are counties and their neighbors that all exhibit above average rates, clustered together in a fashion that would be extremely unlikely to be observed by chance, and conversely for low clusters. There was statistically significant evidence of spatial clustering into high and low rate clusters. The average rate in the high rate clusters (n = 46) was approximately 12 times the average rate in low rate clusters (n = 126), and 2.2 times the national average across all counties. Significant differences were found in the medians of the underlying race, poverty, and urbanicity variables when comparing the low cluster counties with the high cluster counties (p < 0.05). Cluster analysis confirms that IBC rates differ geographically and may be influenced by social and economic environmental factors. Particular attention may need to be paid to race, urbanicity and poverty when considering risk factors for IBC and when developing interventions and alternative prevention strategies.